The VISIONLAB, led by Dr Sarah Bohndiek, uses next-generation imaging sciences to advance our understanding of tumour evolution. We apply the latest spectral imaging hardware, together with biophysical models and machine learning methods, to studies of cancer in both mouse models and patients.
Applications are invited for a postdoctoral research associate to join the VISIONLAB, which is co-located in the Department of Physics and the Cancer Research UK Cambridge Institute at the University of Cambridge. The successful applicant should have a PhD in physical sciences or engineering. They will drive forward a multidisciplinary project advancing the use of Raman spectroscopy. In particular, they will be responsible for pioneering the application of Raman spectroscopy to the study of small molecule metabolites in living cells and tissues.
The successful applicant should be able to demonstrate a strong track record of scientific publication and presentation at international research meetings, commensurate with their research experience. Given the interdisciplinary nature of the laboratory, excellent communication and team working skills are essential. Experience in Raman spectroscopy, including coherent methods such as SRS and CARS, is essential. Practical knowledge of the optical construction of Raman systems, biomedical application of Raman spectroscopy, other live cell multiphoton microscopy methods and/or machine learning for spectral data processing would be advantageous.
Key responsibilities will include: development of advanced Raman spectroscopy methods suitable for application in living cells and tissues; collection and analysis of experimental microscopy data; maintenance and development of our Raman hardware capability; managing a multidisciplinary collaboration across several institutions; development of data processing algorithms that can be used by others working with the technology; and supervision of graduate and undergraduate students in the laboratory.
For more information and to apply see: https://www.jobs.cam.ac.uk/job/37259/